首页> 外文会议>IEEE Vehicular Technology Conference >Efficient Multi-Cell Clustering for Coordinated Multi-Point Transmission with Blossom Tree Algorithm
【24h】

Efficient Multi-Cell Clustering for Coordinated Multi-Point Transmission with Blossom Tree Algorithm

机译:具有开花树算法的有效多点传输的高效多单元聚类

获取原文

摘要

Coordinated multi-point(CoMP) transmission clustering schemes could provide significant gains of system performance, such as throughput and cell-edge user data rates. Due to limitations of the backhaul communication and signal processing capability of base stations(BSs), the intrinsic problem of CoMP is that the selection of which BSs shall cooperate as only a few of BSs can be grouped in a cluster. However, approximating the theoretical performance bound of this clustering problem in CoMP at present is seldom discussed due to its inherent combinatorial complexity. In this paper, a novel efficient multi-cell clustering scheme based on blossom tree algorithm is proposed for cellular networks, incorporating CoMP with two cells in each cluster. With blossom tree algorithm, the proposed scheme can find out the optimal clustering strategy and help the CoMP transmission reach its theoretical performance bound on data rate in real-time computing(milliseconds in MATLAB simulation for one clustering). The simulation results show that our proposed method outperforms the existing dynamic greedy method in terms of cell edge users' average achievable data rate. Besides, it can also maintain high performance when extended to larger clusters in that with 4-cell clustering, the proposed method can reach 23.8% higher data rates than dynamic greedy method.
机译:协调的多点(COMP)传输聚类方案可以提供系统性能的显着增益,例如吞吐量和单元格用户数据速率。由于基站(BSS)的回程通信和信号处理能力的局限性,COMP的内在问题是,在群集中只有少数BS组合的选择该BSS应该协作。然而,近似于当目前在Comp的比赛中的这种聚类问题的理论性能很少讨论其固有的组合复杂性。本文提出了一种基于开花树算法的新型有效的多单元聚类方案,用于蜂窝网络,在每个簇中结合了两个小区的COMP。在开花树算法中,所提出的方案可以找到最佳聚类策略,并帮助Comp传输在实时计算中达到数据速率的理论性能(Matlab模拟中的毫秒为一个聚类)。仿真结果表明,我们所提出的方法在细胞边缘用户的平均可实现数据速率方面优于现有的动态贪婪方法。此外,它还可以在扩展到较大的簇时保持高性能,以4细胞聚类,所提出的方法可以比动态贪婪方法更高的数据速率达到23.8%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号